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- Bekkhus, T., et al.
(author)
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Automated detection of vascular remodeling in tumor-draining lymph nodes by the deep-learning tool HEV-finder
- 2022
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In: Journal of Pathology. - : Wiley. - 0022-3417 .- 1096-9896. ; 258:1, s. 4-11
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Journal article (peer-reviewed)abstract
- Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor-draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high-throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep-learning model and created a graphical user interface for visualization of the results. The tool, named the HEV-finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV-finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large-scale, fully automated, and user-independent, image-based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker. (c) 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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| 2. |
- Khani, Sajjad, et al.
(author)
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Cold-induced expression of a truncated adenylyl cyclase 3 acts as rheostat to brown fat function
- 2024
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In: Nature Metabolism. - 2522-5812.
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Journal article (peer-reviewed)abstract
- Promoting brown adipose tissue (BAT) activity innovatively targets obesity and metabolic disease. While thermogenic activation of BAT is well understood, the rheostatic regulation of BAT to avoid excessive energy dissipation remains ill-defined. Here, we demonstrate that adenylyl cyclase 3 (AC3) is key for BAT function. We identified a cold-inducible promoter that generates a 5′ truncated AC3 mRNA isoform (Adcy3-at), whose expression is driven by a cold-induced, truncated isoform of PPARGC1A (PPARGC1A-AT). Male mice lacking Adcy3-at display increased energy expenditure and are resistant to obesity and ensuing metabolic imbalances. Mouse and human AC3-AT are retained in the endoplasmic reticulum, unable to translocate to the plasma membrane and lack enzymatic activity. AC3-AT interacts with AC3 and sequesters it in the endoplasmic reticulum, reducing the pool of adenylyl cyclases available for G-protein-mediated cAMP synthesis. Thus, AC3-AT acts as a cold-induced rheostat in BAT, limiting adverse consequences of cAMP activity during chronic BAT activation.
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| 4. |
- Partel, Gabriele, 1988-, et al.
(author)
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Automated identification of the mouse brain’s spatial compartments from in situ sequencing data
- 2020
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In: BMC Biology. - : Springer Nature. - 1741-7007. ; 18:1
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Journal article (peer-reviewed)abstract
- Background Neuroanatomical compartments of the mouse brain are identified and outlined mainly based on manual annotations of samples using features related to tissue and cellular morphology, taking advantage of publicly available reference atlases. However, this task is challenging since sliced tissue sections are rarely perfectly parallel or angled with respect to sections in the reference atlas and organs from different individuals may vary in size and shape. With the advent of in situ sequencing technologies, it is now possible to profile the gene expression of targeted genes inside preserved tissue samples and thus spatially map biological processes across anatomical compartments. This also opens up for new approaches to identifying tissue compartments.Results Here, we show how in situ sequencing data combined with dimensionality reduction and clustering can be used to identify spatial compartments that correspond to known anatomical compartments of the brain. We also visualize gradients in gene expression and sharp as well as smooth transitions between different compartments. We apply our method on mouse brain sections and show that computationally defined anatomical compartments are highly reproducible across individuals and have the potential to replace manual annotation based on cell and tissue morphology. Conclusion Mapping the brain based on molecular information means that we can create detailed atlases independent of angle at sectioning or variations between individuals.
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| 5. |
- Partel, Gabriele, et al.
(author)
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Identification of spatial compartments in tissue from in situ sequencing data
- 2024
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Other publication (other academic/artistic)abstract
- Spatial organization of tissue characterizes biological function, and spatially resolved gene expression has the power to reveal variations of features with high resolution. Here, we propose a novel graph-based in situ sequencing decoding approach that improves recall, enabling precise spatial gene expression analysis. We apply our method on in situ sequencing data from mouse brain sections, identify spatial compartments that correspond with known brain regions, and relate them with tissue morphology.
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